Days
146
27
46
40
33
81
16.46
Report
This is a report on 146 days of observation of students absenteeism.
The average absent days 16.4589041.
This report was generated on April 21, 2021.
Created by: DINESH RAJAN R A
Confidential: HIGHLY!
---
title: "20CSEG06"
author: "DINESH RAJAN R A"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
social: ["twitter","facebook","menu"]
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(ggvis)
library(MASS)
```
```{r}
data(quine)
```
```{r}
mycolors=c("blue","#FFC125","darkgreen","darkorange")
```
Interactive Data Visualization
=====================================
Row
-------------------------------------
### Absent Record Analysis
```{r}
valueBox(paste("Days"),
color = "warning")
```
### Absent by Age Group
```{r}
valueBox(length(quine$Age),
icon = "fa-user")
```
### AVg Absent by age group
```{r}
gauge(round(mean(quine$Age),
digits = 2),
min = 0,
max = 350,
gaugeSectors(success = c(0, 150),
warning = c(150, 240),
danger = c(240, 350),
colors = c("green", "yellow", "red")))
```
### F0
```{r}
valueBox(sum(quine$Age == "F0"),
icon = 'fa-building')
```
### F1
```{r}
valueBox(sum(quine$Age == "F1"),
icon = 'fa-building')
```
### F2
```{r}
valueBox(sum(quine$Age == "F2"),
icon = 'fa-building')
```
### F3
```{r}
valueBox(sum(quine$Age == "F3"),
icon = 'fa-building')
```
Row
-------------------------------
### Absent by Age Group
```{r}
d2=quine %>%
group_by(Age) %>%
summarise(Days = n()) %>%
plot_ly(x = ~Age,
y = ~Days,
color = "blue",
type = 'bar') %>%
layout(xaxis = list(title = "Absent By Age Group"),
yaxis = list(title = 'Days'))
d2
```
### Most Absent by Age Group
```{r}
d3=quine %>%
group_by(Age) %>%
summarise(Days = n()) %>%
filter(Days>18) %>%
plot_ly(labels = ~Age,
values = ~Days,
marker = list(colors = mycolors)) %>%
add_pie(hole = 0.2) %>%
layout(xaxis = list(zeroline = F,
showline = F,
showticklabels = F,
showgrid = F),
yaxis = list(zeroline = F,
showline = F,
showticklabels=F,
showgrid=F))
d3
```
### lrn vs Days
```{r}
d4=plot_ly(quine,
x = ~Lrn,
y = ~Days,
text = paste("Lrn:", quine$Lrn,
"Days:",
quine$Days),
type = "bar") %>%
layout(xaxis = list(title="Lrn"),
yaxis = list(title = "Lrn vs Days"))
d4
```
Row
------------------------------------
### boxplot for most absent in days
```{r}
quine %>%
group_by(Age) %>%
ggvis(~Age, ~Days, fill = ~Age) %>%
layer_boxplots()
```
Data Table
========================================
```{r}
datatable(quine,
caption = "Absent Data",
rownames = T,
filter = "top",
options = list(pageLength = 25))
```
Pivot Table
=========================================
```{r}
rpivotTable(quine,
aggregatorName = "Count",
cols= "Days",
rows = "Age",
rendererName = "Heatmap")
```
Summary {data-orientation=columns}
===========================================
Column
-----------------------------------
### Max Absent Days
```{r}
valueBox(max(quine$Days),
icon = "fa-user" )
```
### Average Absent Days
```{r}
valueBox(round(mean(quine$Days),
digits = 2),
icon = "fa-area-chart")
```
Column
---------------------------
Report
* This is a report on `r length(quine$Days)` days of observation of students absenteeism.
* The average absent days `r mean(quine$Days)`.
This report was generated on `r format(Sys.Date(), format = "%B %d, %Y")`.
About Report
========================================
Created by: DINESH RAJAN R A
Confidential: HIGHLY!